Currently set to Index
Currently set to Follow

Use Cases and ResultsThe failure rate was reduced by 28% avoiding the addition of 20 full-time staff at a cost of $2.3 million.

Use Cases and Results92% of incidents were detected prior to customer impact.

Use Cases and ResultsImproved service availability by 60% and reduced staffing requirements by 50%.

Use Cases and ResultsReduced MTTR by 40% for service disruption and by 80% for degradation issues.

APIs / Traps

Fault Management

APIs / Traps

Performance Management

APIs / Traps

Change Assurance

Enhance customer experience, lower cost, and improve operational efficiency with VIA AIOps

VIA AIOps enables a new service assurance operating model and a new way of working through automation powered by real-time analytics, artificial intelligence, and machine learning.

Leading Network Operator uses VIA AIOps for Automated Incident Management
VIA AIOps use case

Transform Fault Management with Process Automation

  • Monitor and analyze syslog, trap, and alarms events from physical and virtual hosts within and across technology layers and applications in real-time
  • Enriches data through contextualization using machine-learned topologies and dimension discovery analysis 
  • Automatically generates baselines for every metric and dimension combination to detect faults more accurately 
  • Aggregates as appropriate multiple signals though process automation that may appear across service domains to a single incident 
  • Process automation powered by AI and machine learning defines probable root cause, symptoms and population impacted for rapid action and resolution 
  • Communicates bidirectionally with service management systems 
An Over-the-Top Video Service Provider Improves Customer Experience with VIA AIOps

Transform Performance Management with Process Automation

  • Monitor and analyze KPI time-series data from elements & applications
  • Unified data collection and analysis in cloud-native environments 
  • Cloud monitoring for performance across clusters vertically and horizontally without human intervention 
  • Detects service performance and customer-impacting incidents earlier with machine-learned baselines, machine-learned topologies, and stochastic modelling 
  • Eliminates multiple teams working on the same root cause through affinity analysis
  • Process automation defines root cause, symptoms and population impacted to enable faster action 
  • Prescribes next best action for incident remediation or prevention  
Top-Tier Cable Operator uses VIA Ops to reduce cost and improve DevOps and change assurance processes
AIOps for content streaming narrative

Transfrom Change Assurance and Improve DevOps and CI/CD Processes

  • Discover dependencies with total ecosystem observability
  • Detect change to an entity’s attribute (e.g., subscriber’s device or element’s firmware)
  • Correlate alarms, events, incidents and change tickets
  • Monitor for and detect customer experience impact
  • Automate response with early anomaly detection resulting from change
  • Improves CI/CD Processes with the addition of AIOps 

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